The main goal of this project is to create a machine learning model in order to quantify liver steatosis in liver donor faster, more objective and reliable than histological analysis and surgeons point-of-view.
Surgeons (junior and senior operators) from the HBP \& Transplantation Unit took the pictures. They were taken after the laparotomy and before any type of surgical procedure. For each deceased donor case, a total of 5 pictures were taken: one for the left lobe and another for the right one before undergoing a surgical biopsy, two more (one for the left and one for the right lobe) after the histological analysis, near to the site of the surgical biopsy, and finally, one picture after liver perfusion.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
246
Liver donors photographed
Concepción Gómez-Gavara
Barcelona, Spain
RECRUITINGThe main goal of this project is to create a machine learning model in order to quantify liver steatosis in liver donor faster, more objective and reliable than histological analysis and surgeons point-of-view.
Accuracy
Time frame: 4 weeks
To build an image dataset to evaluate postransplant liver function.
PDF will be evaluated according to Olthoff criteria
Time frame: 1 week
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